The main body of this research is concerned with both the application to data sets and methodological analysis of cross-lagged panel correlations as used in studies of cognitive development. The technique is used for any set of appropriate data that becomes available either in the form of published correlation matrices or in data from data banks. Comparisons are made between the usual form of analysis in which various measures are studied pair-wise and a form involving cognitive composites. The methodological analyses involve the Monte Carlo procedure in the study of the sampling characteristics of the pair-wise comparisons and the intellectual composite comparisons. Factorial descriptions for the situations in which cross-lagged differences appear are also being investigated by means of a variation of a standard factor analytic methodology. Currently available factor methodologies are not applicable to developmental data. A supplemental project involves analysis of the effects of social selective forces on school attendance as revealed in the intercorrelations of school means.